arXiv Machine Learning June 18, 2026 By David Bertram, Anja Ophey, Sinah R\"ottgen, Konstantin Kufer, Gereon R. Fink, Elke Kalbe, Clint Hansen, Walter Maetzler, Maximilian Kapsecker, Lara M. Reimer, Stephan Jonas, Andreas T. Damgaard, Natasha B. Bertelsen, Casper Skjaerbaek, Per Borghammer, Karolien Groenewald, Pietro-Luca Ratti, Michele T. Hu, No\'emie Moreau, Michael Sommerauer, Katarzyna Bozek

ActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy

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arXiv:2511. 05221v3 Announce Type: replace Abstract: Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of $\alpha$-synucleinopathies, often preceding the clinical onset of Parkinson's disease, dementia with Lewy bodies, or multiple system atrophy.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI

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Learning transferable human physiology from two million hours of sleep with SleepFM-2

SleepFM-2 is a foundation model trained on 282,511 polysomnography recordings, covering over two million hours of multimodal sleep physiology. It outperforms its predecessor in disease prediction, sleep scoring, and event detection, and its representation improves performance across diverse tasks—including wearable sensing, subjective sleep reports, and transfer to other EEG modalities. When combined with age, sex, and BMI, the model meets stringent discrimination criteria for 215 EHR phenotypes, adding reproducible information beyond demographics for 155 of them.

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arXiv AI

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arXiv Machine Learning

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Foundation models for movement data: Are they ready for prime-time?

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arXiv AI

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arXiv Machine Learning

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Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

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arXiv AI

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SleepVLM: A Rule-Grounded Vision-Language Model for Auditable Sleep Staging

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